Skipping field AddressList: unsupported OGR type: 5
Skipping field AddressIdList: unsupported OGR type: 5Interactive map
Interactive Map: Parcels and UnitCounts
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Skipping field AddressList: unsupported OGR type: 5
Skipping field AddressIdList: unsupported OGR type: 5---
title: Interactive map
---
```{python}
import geopandas as gpd
import os
import matplotlib as plt
import folium
from shapely.geometry import mapping
import geopandas as gpd
# List of base names
base_names = ["Fan District Association","Civic_Associations", "Addresses_in_fan", "Parcels_in_fan"]
# Folder where GeoJSON files are located
geojson_folder = "../precious/"
features = ["Addresses","Parcels"]
selector = "Civic_Associations"
selector_key = "Fan District Association"
#selector_key = "West Avenue Improvement Association"
input_folder = "../data"
# Load files into a dictionary
data = {}
for name in base_names:
file_path = os.path.join(input_folder, f"{name}.geojson")
if os.path.exists(file_path):
data[name] = gpd.read_file(file_path)
else:
print(f"⚠️ File not found: {file_path}")
#data[selector_key] = data[selector][ data[selector]["Name"]==selector_key]
```
## Interactive Map: Parcels and UnitCounts
```{python}
# Step 1: Filter addresses with UnitType == None
addresses = data["Addresses_in_fan"]
addresses = addresses[addresses["UnitType"].isna()].copy()
# Ensure both are in the same CRS
addresses = addresses.to_crs(data["Parcels_in_fan"].crs)
# Step 2: Perform spatial join - match addresses within parcels
joined = gpd.sjoin(addresses, data["Parcels_in_fan"], how="inner", predicate="within")
```
```{python}
# Step 3: Group by Parcel ID (or index) and sum UnitCount
# Choose a unique key to group by — use index_right if no parcel ID is available
parcel_unit_counts = (
joined.groupby("ParcelID")["UnitCount"]
.sum()
.rename("SummedUnitCount")
)
```
```{python}
# Step 4: Join the result back to Parcels GeoDataFrame
parcels_with_units = data["Parcels_in_fan"].copy()
parcels_with_units["SummedUnitCount"] = parcel_unit_counts
# Optional: fill NaN with 0 for parcels without addresses
parcels_with_units["SummedUnitCount"] = parcels_with_units["SummedUnitCount"].fillna(0).astype(int)
```
```{python}
fan_shape = data[selector_key].to_crs(epsg=4326) # Folium uses WGS84
# Compute bounds: [[south, west], [north, east]]
minx, miny, maxx, maxy = fan_shape.total_bounds
bounds = [[miny, minx], [maxy, maxx]]
# Center for initial rendering (optional fallback)
center = [(miny + maxy) / 2, (minx + maxx) / 2]
# Create map and set bounds
m = folium.Map(location=center, zoom_start=15, tiles="cartodbpositron")
m.fit_bounds(bounds)
# Add neighborhood boundary
x = folium.GeoJson(
data[selector_key].geometry,
name="The Fan Boundary",
style_function=lambda x: {
"color": "black",
"weight": 3,
"fillOpacity": 0,
}
).add_to(m)
# Add parcels (lighter gray polygons)
x = folium.GeoJson(
data["Parcels_in_fan"].geometry,
name="Parcels",
style_function=lambda x: {
"color": "#999999",
"weight": 0.5,
"fillOpacity": 0.4,
},
).add_to(m)
if 0:
# Step 1: Clip values (saturate above 100)
clip_max = 100
parcels_with_units["ClippedUnits"] = parcels_with_units["SummedUnitCount"].clip(upper=clip_max)
# Step 2: Create colormap from 0 to clip_max
clipped_colormap = cm.linear.YlOrRd_09.scale(0, clip_max)
clipped_colormap.caption = f"Units per Parcel (capped at {clip_max})"
clipped_colormap.add_to(m)
# Step 3: Add to map
folium.GeoJson(
parcels_with_units,
name=f"Units per Parcel (max {clip_max})",
style_function=lambda feature: {
"fillColor": clipped_colormap(feature["properties"]["ClippedUnits"])
if feature["properties"]["ClippedUnits"] else "#ffffff",
"color": "#666666",
"weight": 0.5,
"fillOpacity": 0.7,
},
# tooltip=folium.GeoJsonTooltip(
# fields=["SummedUnitCount", "ClippedUnits"],
# aliases=["Total Units", f"Clipped to {clip_max}"],
# localize=True
# )
).add_to(m)
if 0:
import branca.colormap as cm
colormap = cm.linear.YlOrRd_09.scale(0, parcels_with_units["SummedUnitCount"].max())
colormap.caption = "Units per Parcel (filtered by UnitType=None)"
colormap.add_to(m)
x = folium.GeoJson(
parcels_with_units,
name="Filtered Unit Density",
style_function=lambda feature: {
"fillColor": colormap(feature["properties"]["SummedUnitCount"]) if feature["properties"]["SummedUnitCount"] else "#ffffff",
"color": "#333333",
"weight": 0.5,
"fillOpacity": 0.7,
},
tooltip=folium.GeoJsonTooltip(
fields=["ParcelID", "SummedUnitCount"],
aliases=["Parcel", "Total Units"],
)
).add_to(m)
if 1:
def classify_unit_bin(unit_count):
if unit_count == 0:
return '0'
elif unit_count == 1:
return '1'
elif unit_count == 2:
return '2'
elif unit_count <= 4:
return '3-4'
elif unit_count <= 10:
return '5-10'
elif unit_count <= 20:
return '11-20'
elif unit_count <= 35:
return '21-35'
else:
return '36+'
# Apply to DataFrame
parcels_with_units["UnitBin"] = parcels_with_units["SummedUnitCount"].apply(classify_unit_bin)
# format dollar values
parcels_with_units["FormattedValue"] = parcels_with_units["TotalValue"].apply( lambda x: f"${int(x/1000)}k" if x else "$0k" )
# Define bin colors
bin_colors = {
'0': '#ffffff', # white
'1': '#ffffcc', # light yellow
'2': '#fd8d3c', # orange
'3-4': '#fc4e2a', # darker orange
'5-10': '#e31a1c', # red
'11-20': '#bd0026', # dark red
'21-35': '#800026', # deeper red
'36+': '#4d0018', # very dark red
}
folium.GeoJson(
parcels_with_units,
name="Binned Unit Density",
style_function=lambda feature: {
"fillColor": bin_colors.get(feature["properties"]["UnitBin"], "#cccccc"),
"color": "#666666",
"weight": 0.5,
"fillOpacity": 0.7,
},
tooltip=folium.GeoJsonTooltip(
fields=["ParcelID","SummedUnitCount", "UnitBin"],
aliases=["ParcelID","Total Units", "Bin"],
localize=False
)
).add_to(m)
```
::: {.column-page-inset-right}
```{python}
m.save("../docs/thefan_parcels.html")
m
```
:::